Frame_annotation class

Author: tefenet

examples/make_positions_file.py

@@ -6,18 +6,18 @@
 example_path = osp.join(Path.home(), '.sldatasets')
 # must provide the path of 'lsa64_positions.mat', in this example
 # # ~/.sldatasets/LSA&$_pre
-a_path = osp.join(example_path, 'LSA64_pre')
-positions.positions_mat_to_npz(osp.join(example_path, 'LSA64_pre'))
+# a_path = osp.join(example_path, 'LSA64_pre')
+# positions.positions_mat_to_npz(osp.join(example_path, 'LSA64_pre'))
 
-# # can provide the destiny path of the npz else current dir will be used, in this example
-# # ~/.sldatasets/LSA64_raw
-a_path = osp.join(example_path, 'LSA64_raw')
-positions.get_humans_from_dataset(
-    sld.get('lsa64', version='raw'), a_path)
+# # # can provide the destiny path of the npz else current dir will be used, in this example
+# # # ~/.sldatasets/LSA64_raw
+# a_path = osp.join(example_path, 'LSA64_raw')
+# positions.get_humans_from_dataset(
+#     sld.get('lsa64', version='raw'), a_path)
 
-a_path = osp.join(example_path, 'LSA64_cut')
-positions.get_humans_from_dataset(
-    sld.get('lsa64', version='cut'), a_path)
+# a_path = osp.join(example_path, 'LSA64_cut')
+# positions.get_humans_from_dataset(
+#     sld.get('lsa64', version='cut'), a_path)
 
 a_path = osp.join(example_path, 'ASLLVD_pre')
 positions.get_humans_from_dataset(sld.get('asllvd').data, a_path)

examples/test_basics.py

@@ -1,16 +1,22 @@
 import sldatasets as sld
 
 dataset = sld.get("asllvd")
+print("dataset summary:")
 dataset.summary()
 for video, description in dataset:
+    print('video description:')
     print(description)
     frame, frame_annot = video[3]
-    print(frame.shape)
-    print(frame_annot)
-dataset = sld.get("lsa64", version='pre')
-dataset.summary()
-for video, description in dataset:
-    print(description)
-    frame, frame_annot = video[3]
-    print(frame.shape)
-    print(frame_annot)
+    print('frame shape: ', frame.shape)
+    print('estimated body parts (x,y,score): ')
+    frame_annot.pretty()
+    face = frame_annot.h.get_face_box(640, 480)
+    print('face box: ', face)
+    print(frame_annot.h.get_upper_body_box(640, 480))
+# dataset = sld.get("lsa64", version='pre')
+# dataset.summary()
+# for video, description in dataset:
+#     print(description)
+#     frame, frame_annot = video[3]
+#     print(frame.shape)
+#     print(frame_annot)

positions/__init__.py

@@ -1,7 +1,8 @@
 
+from sldatasets.annotations import Human
 from os import path as osp
 import numpy as np
-from sldatasets.body import Human
+from sldatasets.annotations import Human as H, Frame_annotation as fa, BodyPart
 
 
 def positions_mat_to_npz(path=None):
@@ -94,42 +95,27 @@ def process_video(video, e):
     for j in range(0, n):
         img = video[j, :]
         humans = e.inference(img, True, 4.0)
+        h = H([])
         if len(humans) != 1:
             b = True
         else:
-            h = Human([])
-            h.body_parts = humans[0].body_parts
-            h.score = humans[0].score
-        frames.append(humans)
+            h = translate(humans, h)
+        frames.append(fa(h))
     if b:
         raise InferenceError(frames)
     return frames
 
 
+def translate(humans, h):
+    body = {}
+    for key, part in humans[0].body_parts.items():
+        body[key] = BodyPart(part.uidx, part.part_idx,
+                             part.x, part.y, part.score)
+    h.body_parts = body
+    h.score = humans[0].score
+    return h
+
+
 class InferenceError(Exception):
     def __init__(self, arg):
         self.args = arg
-
-
-def translate_tf_pose_humans(npz_file):
-    from sldatasets.body import Human
-    npz = np.load(npz_file)
-    data = {}
-    for video in npz.files:
-        video_annotation = npz[video]
-        n = video_annotation.size
-        result = np.empty((n,), dtype=object)
-        for i, frame_annotation in enumerate(video_annotation):
-            h = Human([])
-            try:
-                human = frame_annotation[0]
-                h.body_parts = human.body_parts
-                h.score = human.score
-            except:
-                print('frame', str(i), ' of video ', video,
-                      " has no annotations. processing videos wait...")
-            result[i] = h
-        data[video] = result
-    outfile = osp.join(osp.dirname(npz_file), 'positions.npz')
-    np.savez(outfile, **data)
-    return outfile

requirements.txt

@@ -1,6 +1,7 @@
 scikit-video
-matplotlib
+pandas
 gdown
 pathlib
-opencv-python
-tensorflow
+numpy
+openpyxl
+xlrd

setup.py

@@ -1,23 +1,24 @@
 from setuptools import find_packages, setup
 
-REQUIRED_PACKAGES =[
+REQUIRED_PACKAGES = [
     'scikit-video',
-    'matplotlib',
     'gdown',
     'pathlib',
-    'opencv-python',
-    'tensorflow',
+    'openpyxl',
+    'xlrd',
+    'pandas',
+    'numpy',
 ]
 
-PROJECT_URLS={
+PROJECT_URLS = {
     'Tracker': 'https://github.com/midusi/sign_language_datasets/issues',
     'Documentation': 'https://github.com/midusi/sign_language_datasets/wiki',
     'Source': 'https://github.com/midusi/sign_language_datasets',
 }
 
 setup(
     name='sldatasets',
-    version='0.0.1',
+    version='0.0.2',
     author='Pablo Kepes and Facundo Quiroga',
     author_email="[email protected]",
     description=(
@@ -28,9 +29,10 @@
     project_urls=PROJECT_URLS,
     packages=find_packages(),
     install_requires=REQUIRED_PACKAGES,
-    #zip_safe=False,
+    # zip_safe=False,
     classifiers=[
-        'Development Status :: 2 - Pre-Alpha',
+        'Development Status :: 3 - Alpha',
+        'Intended Audience :: Science/Research',
         'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
         'Programming Language :: Python :: 3',
         'Programming Language :: Python :: 3.7',

sldatasets/Datasetloader.py

@@ -69,7 +69,7 @@ def load_annotations(self):
             from gdown import download
             logging.info(f"Dowloading Positions to {outfile}")
             download(self.x.get_pos_url(), outfile, quiet=False)
-        return np.load(outfile)
+        return np.load(outfile, allow_pickle=True)
 
 
 class LSA64(Datasetloader):

sldatasets/body.py sldatasets/annotations.py

@@ -13,6 +13,22 @@ def _include_part(part_list, part_idx):
     return False, None
 
 
+class Frame_annotation(object):
+
+    def __init__(self, hum):
+        self.h = hum
+
+    def get(self):
+        dic = {}
+        for part in self.h.body_parts.values():
+            dic[part.get_part_name().name] = (part.x, part.y, part.score)
+        return dic
+
+    def pretty(self):
+        import pprint
+        pprint.pprint(self.get())
+
+
 class Human:
     """
     body_parts: list of BodyPart

sldatasets/video_dataset.py

@@ -18,13 +18,15 @@ def send(self, ignored_arg):
         anotation = self.loader.load_annotations()
         anot_index = specs['filename'].split('.')[0]
         try:
-            for i, human in enumerate(anotation[anot_index]):
-                l.append((frames[i], human))
+            for i, man in enumerate(anotation[anot_index]):
+                l.append((frames[i], man))
             return (l, specs)
         except TypeError:
             for f in frames:
                 l.append((f, anotation[anot_index]))
             return (l, specs)
+        except ModuleNotFoundError:
+            print(anotation[anot_index].__class__)
 
     def throw(self, type=None, value=None, traceback=None):
         raise StopIteration